Responsibilities:

Develop, deploy, and maintain robust machine learning models using traditional techniques (e.g., scikit-learn) to support AI-driven operations.Conduct root cause analyses to identify and resolve data inconsistencies and performance bottlenecks.Collaborate extensively across engineering, product, and business teams to align AI solutions with operational goals.Integrate Gen AI capabilities (LLMs, SLMs, Agents) using frameworks like LangChain and LangGraph to enhance automation and decision-making.Create insightful visualizations and dashboards to communicate findings and model performance.Participate in feature engineering and model tuning to improve accuracy and reliability.Ensure data integrity and consistency across multiple sources and systems.Mentor junior team members and foster a culture of continuous learning and innovation.

Skills:

Python Expertise: Advanced proficiency in Python for data manipulation, modeling, and automation.Traditional ML: Strong hands-on experience with scikit-learn and other classical ML libraries.Gen AI Knowledge: Familiarity with LLMs, SLMs, and agent-based architectures using LangChain, LangGraph, or similar tools.Data Engineering: Experience building and optimizing data pipelines and workflows.Visualization: Skilled in tools like Matplotlib, Seaborn, Power BI, or Tableau.Database Proficiency: Strong SQL and working knowledge of NoSQL databases.Communication: Ability to clearly articulate technical concepts to non-technical stakeholders.Collaboration: Proven ability to coordinate across teams and manage dependencies effectively.Mentorship: Experience guiding junior data scientists and contributing to team development.

Level Criteria – T3 (Internal Use Only):

Demonstrates deep conceptual and practical knowledge in data science and adjacent technical domains.Applies best practices and understands competitive and market differentiators.Solves complex problems independently, using judgment informed by multiple data sources.Operates with minimal supervision; may lead projects or own critical operational initiatives.Influences project outcomes across teams and serves as a go-to resource for peers.Communicates complex or sensitive information effectively and builds consensus across stakeholders.Represents a stable career level with opportunities for long-term growth and impact.

EDUCATION AND EXPERIENCE
·       Bachelor's degree (B.E/ B Tech. computer science, engineering, statistics/mathematics or a related
field) from a four-year college or university, or equivalent, master’s a plus.
·       Total at least 5+ years of experience working on enterprise AI products
·       Experience in supporting software products or applications in the AI ML domain.
·       The above statements are intended to describe the general nature and level of work being performed
by most people assigned to this job. They are not intended to be an exhaustive list of all duties and
responsibilities and requirements

Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.